Paper Citation Record · LEDGER

Towards Interpretable Time Series Foundation Models

As of 14 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2507.07439.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.07439 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:44:42.080260Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

verified exact1
verified fuzzy1
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e7c2f65c-1060-47ec-8c47-f8b0de6203db · outbound

This paper cites TimeSeriesExam: A time series understanding exam.

Towards Interpretable Time Series Foundation Models TimeSeriesExam: A time series understanding exam

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:40.613192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 277363d2-f25c-4e52-b6bb-78860829d5a8 · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

Towards Interpretable Time Series Foundation Models A decoder-only foundation model for time-series forecasting

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:40.690009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57c0e333-54af-46fd-93a5-5f942bdc2a32 · outbound

This paper cites Plots Unlock Time-Series Understanding in Multimodal Models.

Towards Interpretable Time Series Foundation Models Plots Unlock Time-Series Understanding in Multimodal Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:40.748573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dcdde1e-2470-4ce2-8992-baa7159fa629 · outbound

This paper cites UniTS: A Unified Multi-Task Time Series Model.

Towards Interpretable Time Series Foundation Models UniTS: A Unified Multi-Task Time Series Model

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.050039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19c89c08-3dea-4e58-b568-fad49162b233 · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

Towards Interpretable Time Series Foundation Models MOMENT: A Family of Open Time-series Foundation Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.145511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9f77947-5859-4a08-9a9c-8f13c5710a71 · outbound

This paper cites Large Language Models Are Zero-Shot Time Series Forecasters.

Towards Interpretable Time Series Foundation Models Large Language Models Are Zero-Shot Time Series Forecasters

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.205360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08dc4464-3cf2-4239-af5d-a5bb4379dcf9 · outbound

This paper cites Textbooks Are All You Need.

Towards Interpretable Time Series Foundation Models Textbooks Are All You Need

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.274393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c12ce80-8c79-4c3c-9ba1-c680f6eab115 · outbound

This paper cites Position: What Can Large Language Models Tell Us about Time Series Analysis.

Towards Interpretable Time Series Foundation Models Position: What Can Large Language Models Tell Us about Time Series Analysis

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.454694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84566d22-73ba-43d8-9ea6-95a17dae210e · outbound

This paper cites Qwen2.5 Technical Report.

Towards Interpretable Time Series Foundation Models Qwen2.5 Technical Report

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.510612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cf5075b-6260-4b8a-aa23-bbe578f2a6c6 · outbound

This paper cites Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting.

Towards Interpretable Time Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.565840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cf19e96-a6ac-4405-9cc4-73cfa4f2fe10 · outbound

This paper cites The first step is the hardest: Pitfalls of Representing and Tokenizing Temporal Data for Large Language Models.

Towards Interpretable Time Series Foundation Models The first step is the hardest: Pitfalls of Representing and Tokenizing Temporal Data for Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.647677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53499234-23df-4f1c-8e5c-33597573abbe · outbound

This paper cites 5 Submission and Formatting Instructions for ICML 2025 Wah, E., Wright, M., and Wellman, M.

Towards Interpretable Time Series Foundation Models 5 Submission and Formatting Instructions for ICML 2025 Wah, E., Wright, M., and Wellman, M

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:44:42.938100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 319dbaf1-f8bd-46d0-8593-5edefeefbf98 · outbound

This paper cites Unified Training of Universal Time Series Forecasting Transformers.

Towards Interpretable Time Series Foundation Models Unified Training of Universal Time Series Forecasting Transformers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.887615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebd55fdd-4f16-4d22-8b0d-ec83b982c38e · outbound

This paper cites A Survey on Knowledge Distillation of Large Language Models.

Towards Interpretable Time Series Foundation Models A Survey on Knowledge Distillation of Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.924652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c03f2d15-1fd9-43c4-a042-e11062ef6b4e · outbound

This paper cites How well do Large Language Models perform in Arithmetic tasks?.

Towards Interpretable Time Series Foundation Models How well do Large Language Models perform in Arithmetic tasks?

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:42.016394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f19df82-b1b2-469a-be7b-8e659e76b8bb · outbound

This paper cites Can LLMs Understand Time Series Anomalies?.

Towards Interpretable Time Series Foundation Models Can LLMs Understand Time Series Anomalies?

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:42.080260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1d1f308-3944-49a6-89dd-c0fb90f55df2 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Towards Interpretable Time Series Foundation Models Distilling the Knowledge in a Neural Network

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.366928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1abb3a5c-09e7-4ded-b36b-55e76e36afc7 · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

Towards Interpretable Time Series Foundation Models A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:41.804246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afc53277-9cd4-480c-9a3d-59e649cf8c24 · outbound

This paper cites an unresolved cited work.

Towards Interpretable Time Series Foundation Models Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:44:43.126100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 38ee58f9-6f46-4bfc-9076-203b163a9ec9 · outbound

This paper cites TinyStories: How Small Can Language Models Be and Still Speak Coherent English?.

Towards Interpretable Time Series Foundation Models TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:40.930687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 969d680b-d734-4d71-9849-c6233f3d9273 · outbound

This paper cites Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections.

Towards Interpretable Time Series Foundation Models Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:44:42.806294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 99ed5618-85e3-406e-83be-bcb1cc62b05c · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Towards Interpretable Time Series Foundation Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T18:44:40.848478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.